def test_array_to_duplicated_b(self) -> None:
a = np.array([[50, 50, 32, 17, 17], [2, 2, 1, 3, 3]])
# find duplicate rows
post = array_to_duplicated(a, axis=0)
self.assertEqual(post.tolist(), [False, False])
post = array_to_duplicated(a, axis=1)
self.assertEqual(post.tolist(), [True, True, False, True, True])
post = array_to_duplicated(a, axis=1, exclude_first=True)
self.assertEqual(post.tolist(), [False, True, False, False, True])
def test_array_to_duplicated_d(self) -> None:
c = array_to_duplicated(
np.array(['q','q','q', 'a', 'w', 'w'], dtype=object),
exclude_first=False,
exclude_last=False
)
self.assertEqual(c.tolist(), [True, True, True, False, True, True])
def test_array_to_duplicated_a(self) -> None:
a = array_to_duplicated(
np.array([0,1,2,2,1,4,5,3,4,5,5,6]),
exclude_first=False,
exclude_last=False
)
self.assertEqual(a.tolist(),
[False, True, True, True, True, True, True, False, True, True, True, False])
a = array_to_duplicated(
np.array([0,1,2,2,1,4,5,3,4,5,5,6]),
exclude_first=True,
exclude_last=False
)
self.assertEqual(a.tolist(),
[False, False, False, True, True, False, False, False, True, True, True, False])
def test_array_to_duplicated(self, array: np.ndarray) -> None:
if array.ndim == 2:
for axis in (0, 1):
post = util.array_to_duplicated(array, axis=axis)
if axis == 0:
unique_count = len(set(tuple(x) for x in array))
else:
unique_count = len(
set(tuple(array[:, i]) for i in range(array.shape[1])))
if unique_count < array.shape[axis]:
self.assertTrue(post.sum() > 0)
else:
post = util.array_to_duplicated(array)
# if not all value are unique, we must have some duplicated
if len(set(array)) < len(array):
self.assertTrue(post.sum() > 0)
self.assertTrue(post.dtype == bool)
def test_array_to_duplicated_c(self) -> None:
a = np.array([[50, 50, 32, 17, 17], [2,2,1,3,3]])
with self.assertRaises(NotImplementedError):
# axis cannot be None
array_to_duplicated(a, axis=None) # type: ignore